Engineering Manager: Engineering Data Platform Enablement (Hybrid, Seattle - WA)
$166,000–$258,000 year
HybridSeattle, Washington, United States
Job Summary
Lead engineering delivery across BigQuery, Looker, Metabase, and AWS workloads while owning platform reliability, incident response, and on-call rotation. Drive capacity planning, manage compute costs, and oversee the deprecation of legacy platforms. Establish LookML governance standards, define access policies, and lead cost optimization initiatives with finance and security partners. Enable conversational analytics through Golden Query standards and agent development while managing token utilization. Set technical direction for architecture and standards, coach engineers on AI fluency, and contribute hands-on by writing code and reviewing pull requests. Partner with product teams to drive enterprise-wide adoption of AI-first engineering practices.
Required Qualifications
- 2+ years leading engineering teams, with direct accountability for delivery and people development
- 5+ years building software, platforms, infrastructure, or data systems
- Hands-on Python proficiency (or equivalent) you still write today — direct technical contribution is expected
- Strong cloud experience across GCP and/or AWS, with fluency in Git, CI/CD, and infrastructure as code
- Experience owning access management programs at scale
- Daily use of AI coding tools and a real point of view on how they change the way teams work
Desired Qualifications
- Data platform or BI depth: BigQuery, Looker, Metabase, Tableau, or MicroStrategy
- Terraform and Kubernetes
- Cloud cost optimization at scale
- Analytics access provisioning in SailPoint IdentityNow via SCIM group synchronization
- Hands-on Dataplex zone governance
- Experience standing up an AI-first engineering practice
- Familiarity with Conversational Analytics, LLM-powered data tools, or semantic layer patterns
- Experience at a large-scale retail, e-commerce, or consumer organization
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